Page 503 - Jolliffe I. Principal Component Analysis
P. 503

Index
                              468
                              metrics 42, 59, 60, 185, 189, 210,
                                                                      scaling or ordination
                                    220, 260, 325, 331, 373, 382,
                                                                      techniques
                                    386–388                     multidimensional scaling see
                                optimal metric 387              multilevel models 353
                              minimax components 267            multiple correlation coefficient 25,
                                        2
                              minimum χ test 120                      141, 143, 174, 177, 191, 197,
                              minimum description length 19,          198, 403
                                    39, 395                     multiple correspondence analysis,
                              minimum spanning tree (MST)             see correspondence analysis
                                    81–83, 130                  multiple regression, see regression
                              minimum variance ellipsoids 267         analysis
                              misclassification probabilities, see  multivariate analysis of variance
                                    discriminant analysis             (MANOVA) 102, 351, 353
                                                                multivariate normal distribution 8,
                              missing data 60, 61, 83, 134, 339,
                                                                      16, 18, 20, 22, 33, 39, 47–55,
                                    363–366, 412
                                                                      60, 69, 119, 152, 155–157,
                                estimating covari-
                                                                      160, 201, 207, 220–222, 236,
                                    ance/correlation
                                                                      239, 244, 254, 264, 267, 276,
                                    matrices 363–365
                                                                      299, 338, 339, 365, 367, 368,
                                estimating PCs 365, 385
                                                                      379, 386, 388
                                in biplots 103, 104
                                                                  curvature 395
                                in designed experiments 353, 365
                                                                  see also contours of constant
                                in regression 363
                                                                      probability, inference for
                              mixtures of distributions 61, 165,      PCs
                                    200, 221, 222, 241, 364
                                                                multivariate regression 17, 183,
                              modal dispersion matrix 395
                                                                      223, 228–230, 331, 352
                              models for PCA 50, 54, 59–61, 119,
                                                                multiway PCA, see three-mode
                                    124–126, 132, 151, 158–160,
                                                                      PCA
                                    220, 364, 369, 405
                                see also fixed effects model for  near-constant relationships
                                    PCA                               between variables 3, 13, 27,
                              modified principal components 144        28, 42–44, 119, 138, 167,
                              most correlated components 26           181, 182, 189, 235, 374, 377,
                              multichannel singular spectrum          378
                                    analysis (MSSA) 302, 305,   nearly equal eigenvalues 43, 262,
                                    307, 308, 310, 311, 316, 329      263, 276, 277, 360, 408, 410
                              multicollinearities 167, 168,       see also stability
                                    170–173, 177, 180, 181, 185,  neural networks 200, 266, 373,
                                    188, 196, 286, 378                379–381, 388, 400, 401, 405,
                                predictive and non-predictive         408, 412–414
                                    multicollinearities 180, 181,  analogue/digital 414
                                    185, 188                      autoassociative 381
                                variance inflation factors (VIFs)  biological plausibility 413
                                    173, 174                      first or last PCs 400, 413
                                see also ill-conditioning         input training net 381
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